Systems and methods of identifying motion of a subject

ABSTRACT

Systems and methods of identifying medical disorders in one or more subjects are disclosed herein. In one embodiment, sound is transmitted toward a subject and at least a portion of the sound reflected by the subject and is acquired as echo data. The acquired echo data is used to generate a motion waveform having a plurality of peaks detected therein. At feast a portion of the plurality of peaks may be indicative of movement of the subject. One or more medical disorders in the subject can be identified based on, for example, time durations and/or amplitude changes between peaks detected in the motion waveform.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application claims the benefit of pending U.S. ProvisionalApplication No. 62/089,130, filed Dec. 8, 2014, and U.S. ProvisionalApplication No. 62/152,519, filed Apr. 24, 2015. The foregoingapplications are incorporated herein by reference in their entireties.

TECHNICAL FIELD

The present technology relates generally to identifying motion of aportion of a subject's body and associated methods and systems. Inparticular, several embodiments are directed to methods of trackingmotion of a subject's body for use in identifying sleep apnea, althoughthese or similar embodiments may be used in identifying chronicobstructive pulmonary disease (COPD), monitoring infant respirationand/or detecting other movements of the subject.

BACKGROUND

Sleep apnea is a common medical disorder that occurs when breathing isdisrupted during sleep. Sleep apnea is estimated to affect nearly 1 in20 American adults and is linked to attention deficit/hyperactivitydisorder, high blood pressure, diabetes, heart attack, stroke andincreased motor vehicle accidents. Sleep apnea is commonly diagnosed ina dedicated sleep clinic that administers polysomnography tests. In apolysomnography test, a trained technician attaches and monitors sensorson the subject for the duration of the subject's sleep over a singlenight. Polysomnography tests, however, can be expensive, time-consumingand labor-intensive, and subjects may have to wait several weeks toreceive a polysomnography test due to long wait lists. Alternatively, ahome sleep apnea test (HSAT) may be performed using a portable recordingsystem in a subject's home, typically during a single night's sleep.During an HSAT, the subject still typically wears several measurementinstruments connected to the portable recording system. Such home testscan also be problematic. For example, improper attachment of one or moreof the measurement instruments may affect the accuracy of a home sleeptest.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of a device shown adjacent a human subjectand configured in accordance with embodiments of the present technology.

FIG. 2 is a block diagram of a system configured in accordance withembodiments of the present technology.

FIG. 3 is a flow diagram of a process configured in accordance with anembodiment of the present technology.

FIG. 4A is a graph depicting a motion waveform acquired in accordancewith an embodiment of the present technology.

FIG. 4B is a graph depicting peaks detected in a motion waveform inaccordance with an embodiment of the present technology.

FIG. 5A is a graph depicting a prior art method of acquiring data.

FIG. 5B is a graph depicting a method of acquiring data in accordancewith an embodiment of the present technology.

FIG. 6 is a flow diagram of a process configured in accordance with anembodiment of the present technology.

FIG. 7 is a flow diagram of a process configured in accordance with anembodiment of the present technology.

FIGS. 8A-8C are graphs showing examples of apnea and hypopnea events inaccordance with an embodiment of the present technology.

DETAILED DESCRIPTION

The present technology relates generally to identifying motion of aportion of a subject's body and associated methods and systems. In oneembodiment of the present technology, for example, a method ofidentifying sleep apnea events in a subject includes transmitting soundenergy toward the subject using a first transducer (e.g., a loudspeaker)and receiving echoes from the subject corresponding to the transmittedsound energy using a second transducer (e.g., a microphone). Electricalsignals corresponding to the echoes are used to generate a waveform anda plurality of peaks can be detected in the waveform. Individual peaksin the waveform can have corresponding amplitudes indicative of abreathing motion of the subject. An indication of a sleep apnea eventcan be output for each occurrence of a period of time between successiveindividual peaks in the waveform exceeding a predetermined thresholdtime. In some aspects, transmitting the sound energy comprises emittinga plurality of audio chirps from the first transducer that linearlysweep from a first frequency (e.g., about 18 kHz) to a second, higherfrequency (e.g., about 20 kHz or higher) over a predetermined timeduration (e.g., between about 5 ms and about 15 ms, about 10.75 ms).

In another embodiment of the present technology, a method of operatingan electronic device to monitor movements of a subject proximate theelectronic device includes emitting a plurality of audio sweep signalstoward the subject from a loudspeaker operatively coupled to theelectronic device. The individual audio sweep signals linearly sweepfrom a first frequency less than 20 kHz (e.g., about 18 kHz) to asecond, higher frequency (e.g., about 20 kHz or higher) over apredetermined time duration (e.g., between about 5 ms and about 15 ms,about 10.75 ms). The method further includes acquiring audio data at amicrophone operatively coupled to the electronic device. The audio datacan include echo signals corresponding to individual audio sweep signalsbackscattered by the subject toward the microphone. The acquired audiodata is processed to generate a motion waveform. One or more peaksdetected in the motion waveform are indicative of movements of thesubject. The method also includes outputting an indication of movementof the subject (e.g., motion of the subject's chest or abdomen) basedone or more of the detected peaks. In some aspects, for example, atleast a portion of the plurality of the audio sweep signals comprisefrequency-modulated continuous-wave sound signals. In some aspects, themethod also includes calculating a plurality of frequency domainrepresentations of the echo signals that are calculated over a timeperiod lasting a predetermined multiple (e.g., 10) of the predeterminedtime duration (e.g., 10.75 ms) of the individual audio sweep signals. Insome aspects, the method can include determining a frequency shift inthe individual frequency domain representations relative to the firstfrequency.

In yet another embodiment of the present technology, a computer programproduct comprising computer usable program code executable to performoperations for outputting an indication of a sleep apnea event in asubject. The operations include transmitting a plurality of chirpsignals to a first transducer (e.g., a loudspeaker) operatively coupledto a mobile device. The individual chirp signals linearly sweep from afirst frequency less than 20 kHz (e.g., 10 kHz, 16 kHz, 18 kHz) to asecond, higher frequency (e.g., 19 kHz, 20 kHz, 22 kHz, 30 kHz) over apredetermined time duration (e.g., 5 ms, 10 ms, 20 ms, 30 ms). Theoperations further include acquiring echo data from a second transducer(e.g., a microphone) operatively coupled to the mobile device. The echodata includes data corresponding to individual chirp signals reflectedby the subject toward the second transducer. The operations also includedemodulating the acquired echo data to obtain a motion signal indicativeof respiratory motion of the subject, and detecting one or moreamplitude peaks in the motion signal. The operations further compriseoutputting an indication of a sleep apnea event if a period of timebetween successive individual amplitude peaks in the motion signalexceeds a predetermined threshold time. In some aspects, the operationscan further include repeating the transmitting and acquiring for apredetermined number of transmit/acquisition cycles. In some aspects,the demodulating the acquired echo data can include performing a singleFourier transform over the predetermined number of transmit/acquisitioncycles.

These and other aspects of the present disclosure are described ingreater detail below. Certain details are set forth in the followingdescription and in FIGS. 1-8C to provide a thorough understanding ofvarious embodiments of the disclosure. Other details describingwell-known systems and methods often associated with motion trackingand/or identification have not been set forth in the followingdisclosure to avoid unnecessarily obscuring the description of thevarious embodiments.

In the Figures, identical reference numbers identify identical, or atleast generally similar, elements. To facilitate the discussion of anyparticular element, the most significant digit or digits of anyreference number refers to the Figure in which that element is firstintroduced. For example, element 110 is first introduced and discussedwith reference to FIG. 1. Many of the details, dimensions, angles andother features shown in the Figures are merely illustrative ofparticular embodiments of the disclosed technology. Accordingly, otherembodiments can have other details, dimensions, angles and featureswithout departing from the spirit or scope of the disclosure. Inaddition, those of ordinary skill in the art will appreciate thatfurther embodiments of the invention can be practiced without several ofthe details described below.

Devices and Methods for Detecting Motion of a Subject

FIG. 1 is a schematic diagram of a device 110 configured in accordancewith embodiments of the present technology. The device 110 is positionednear a human subject 101 lying on a bed 104 such that the subject'sabdomen 102 and chest 103 are approximately a distance D (e.g., 1 meter)from the device 110. A first transducer 115 (e.g., a loudspeaker) isconfigured to emit acoustic energy (e.g., sounds between about 20 Hz and20 kHz or higher), including sound 105. A second transducer 116 (e.g., amicrophone) is configured to receive acoustic energy including reflectedsound 106 received from the subject's body 102. A communication link 113(e.g., an antenna) communicatively couples the device 110 to acommunication network (e.g., the Internet, a cellular telecommunicationsnetwork, a WiFi network). A user interface 118 is configured to receiveinput from the subject 101 and/or another user, and is furtherconfigured to provide visual output to the subject 101 and/or anotheruser. In the illustrated embodiment of FIG. 1, the user interface 118comprises a touchscreen display. In some embodiments, the user interface118 may include, for example, one or more keypads, touchpads,touchscreens, trackballs, mice and/or additional user interface devicesor systems (e.g., a voice input/output system). Moreover, in someembodiments, one or more additional speakers 125 and one or moreadditional microphones 126 may optionally be positioned near the bed 104separate from the device 110, and communicatively coupled to the device110 via the communication link 113 and/or another communication link. Insome other embodiments, the device 110 may include one or moreadditional speakers and/or microphones (not shown).

In the illustrated embodiment of FIG. 1, the device 110 is a depicted asa mobile phone (e.g., a smartphone). In other embodiments, however, thedevice 110 may comprise any suitable electronic device such as, forexample, a tablet, a personal display assistant, a laptop computer, adesktop computer, a set top box and/or another electronic deviceconfigured to transmit and receive sound. In certain embodiments, thedevice 110 may comprise a component of one or more systems and/ordevices (e.g., a baby monitor, a security system, an automobileentertainment system, a stereo system, a home intercom system, a clockradio). Moreover, in the illustrated embodiment of FIG. 1, the subject101 (e.g., a human adult, a human child, an animal) is shown lyingasleep on the bed 104 (e.g., a bed in the subject's bedroom, a bed in amedical facility, a bed in a sleep laboratory). In other embodiments,however, the subject 101 may be awake and/or upright. In someembodiments, the device 110 may be configured to emit the sound 105toward and receive the reflected sound 106 from one or more additionalsubjects (not shown).

In operation, the device 110 generates audio signals—including, forexample, frequency modulated continuous wave (FMCW) audio signals—thatsweep from a first frequency (e.g., about 18 kHz) to a second frequency(e.g., about 20 kHz). The first transducer 115 transmits the generatedaudio signals as the sound 105 toward the subject 101. A portion of thesound 105 is reflected and/or backscattered by the subject's chest 103and/or abdomen 102 toward the second transducer 116 as the reflectedsound 106. The second transducer 116 receives the reflected sound 106and converts it into one or more reflected audio signals. As discussedin further detail below in reference to FIGS. 3-5 and 6B, the device 110can be configured to detect peaks in the reflected audio signals thatcorrespond to movements of the subject's chest 103 and/or abdomen 102.And as discussed in further detail below in reference to FIGS. 3 and7-8C, the device 110 can be further configured to identify and/ordisambiguate one or more apnea events (e.g., a central apnea event, anobstructive apnea event, a hypopnea event) in the subject based on thedetected peaks. In some embodiments, the device 110 is also configuredto identify movements of the subject's chest 103 and/or abdomen 102 thatcorrespond to movements associated with chronic obstructive pulmonarydisease (COPD) or infant respiration.

As those of ordinary skill in the art will appreciate, conventionalapproaches to the identification of sleep disorders and/or other medicaldisorders can include overnight stays at a medical facility usingdedicated (and often expensive) medical equipment. One conventionalapproach is a clinical polysomnography (PSG) test, which istraditionally used to diagnose sleep apnea and other sleep disorders. APSG is typically conducted overnight in a sleep laboratory where atrained technician monitors a subject's sleeping patterns. Thetechnician attaches a number of sensors to the subject including, forexample, a chest and abdomen belt to measure breathing movements, anasal pressure transducer and thermistor, a snore microphone, a pulseoximeter to measure oxygen saturation, a movement sensor on each leg todetect movements, a sensor to determine muscular tone of the chin,sensors to monitor eye movements and/or EEG sensors to measure brainactivity. The sensors are all connected using wires and the technicianmonitors the live data stream from the sensors throughout the sleepduration.

One metric used for sleep apnea identification is the Apnea-HypopneaIndex (AHI), which represents a rate at which apnea and hypopnea eventsoccur during a sleep period. Physicians can classify the sleep apnealevel using AHI values. For example, AHI values ranging from 0 to 5 aretypically classified as no-apnea; AHI values between 5 and 15 aretypically classified as mild-apnea; AHI values between 15 and 30 aretypically classified as moderate-apnea and AHIs of 30 or higher aretypically classified as severe apnea. The apnea-hypopnea index cancomputed as follows:

$\begin{matrix}{{AHI} = \frac{{\# \mspace{14mu} {central}\mspace{14mu} {apnea}} + {\# \mspace{14mu} {hypopnea}} + {\# \mspace{14mu} {obstructive}{\mspace{11mu} \;}{apnea}}}{{total}\mspace{14mu} {sleep}\mspace{14mu} {time}}} & (1)\end{matrix}$

In equation 1 above, central apnea, hypopnea, and obstructive apneacorrespond to the parameters that are tracked during a typical PSGstudy. To compute these parameters, the sensor data collected during thesleep period (typically 6-8 hours) is split into 30-second intervalscalled epochs. The scoring process of analyzing these epochs may involvetwo steps. A first step is staging, which identifies whether the subjectis awake or asleep in each epoch and if asleep, what sleep stage ispresent. This is achieved by examining the brain activity obtained fromthe EEG sensors and the chin tone and eye movement sensor information.At the end of this step, each epoch can be marked as being in either awake or sleep stage. A second step involves identifying the number ofcentral apnea, hypopnea, and obstructive apnea events, using AmericanAcademy of Sleep Medicine (AASM) guidelines. For example, a centralapnea event can occur when the subject holds her breath for anon-negligible duration. A hypopnea event can occur, for example, whenthe subject's chest motion drops by more than 30% with an accompanying4% oxygen desaturation. A hypopnea may also be determined by presence ofa 3% desaturation or an “arousal” (abrupt frequency change) on the EEG.An obstructive apnea event can occur, for example, when the subjectmakes an increased effort to pull air into the lungs but only a minimalamount of air reaches the lungs due to blockage.

As those of ordinary skill in the art will appreciate, polysomnographyprocedures for sensor data collection and processing can be both laborand time intensive. For example, it may take about an hour for thetechnician to fit each subject with sensors typically employed in a PSGmeasurement. Further, throughout a sleep duration (e.g., an eight-hoursleep duration), the technician may continue to monitor the sensors andconfirm the sensors remain properly attached to the subject's body.Sensor data is typically processed manually to tag every epoch with thesleep apnea events. Moreover, while an HSAT may be performed in asubject's home, the test still requires attaching sensors to the subjectthat include, for example, chest and abdomen belts, nasal pressuresensors, transducer and thermistors, EKG sensors, pulse oximetrysensors, and/or pulse arterial tonometry sensors. Home testing can havea high failure rate (e.g., 33%) due to signal loss resulting fromdetachment of wires and cables

In contrast to these conventional approaches outlined above, thedisclosed technology is expected to be considerably less labor intensiveand time consuming. For example, the disclosed techniques for detectingmovement of at least a portion of the subject's body (e.g., a chest, anabdomen) use sound waves without sensors in contact with the subject.The disclosed technology accordingly eliminates the use of wires orcables that may cause test failure due to improper attachment and/orsignal loss. The disclosed technology is also expected provide a benefitof identifying one or more medical conditions (e.g., sleep apnea, COPD)while the subject sleeps or rests in his or her own bed and uses arelatively inexpensive device (e.g., the subject's own smartphone oranother personal electronic device, a computer, an off-the-shelf mobiledevice, etc.). As a result, the disclosed technology can reduce oreliminate the time and/or expenses associated with a technicianmonitoring the subject during an entire sleep duration. The disclosedtechnology is further expected to allow concurrent monitoring andmovement detection of multiple subjects via a single device.

In some embodiments, the disclosed technology can also be utilized inthe identification of a potential presence of COPD in a subject. Asthose of ordinary skill in the art will appreciate, COPD is a chronicinflammatory lung disease that causes obstructed airflow from the lungs.Symptoms of COPD can include breathing difficulty, coughing, sputumproduction and wheezing. COPD exacerbations can involve an acuteworsening of the patient's condition and can be a major cause ofmorbidity and mortality associated with this disease. Increasedrespiratory frequency and reduced tidal volume are common physiologicalcharacteristics of COPD exacerbations. The disclosed technology canassess the frequency and depth of breathing in real time to identifyCOPD exacerbations in the early stages. Such early detections andcorresponding treatment are expected to help prevent worsening of thiscondition.

Suitable Systems

The following discussion provides a brief, general description of asuitable environment in which the technology may be implemented.Although not required, aspects of the technology are described in thegeneral context of computer-executable instructions, such as routinesexecuted by a general-purpose computer. Aspects of the technology can beembodied in a special purpose computer or data processor that isspecifically programmed, configured, or constructed to perform one ormore of the computer-executable instructions explained in detail herein.Aspects of the technology can also be practiced in distributed computingenvironments where tasks or modules are performed by remote processingdevices, which are linked through a communication network (e.g., awireless communication network, a wired communication network, acellular communication network, the Internet, a short-range radionetwork (e.g., via Bluetooth)). In a distributed computing environment,program modules may be located in both local and remote memory storagedevices.

Computer-implemented instructions, data structures, screen displays, andother data under aspects of the technology may be stored or distributedon computer-readable storage media, including magnetically or opticallyreadable computer disks, as microcode on semiconductor memory,nanotechnology memory, organic or optical memory, or other portableand/or non-transitory data storage media. In some embodiments, aspectsof the technology may be distributed over the Internet or over othernetworks (e.g. a Bluetooth network) on a propagated signal on apropagation medium (e.g., an electromagnetic wave(s), a sound wave) overa period of time, or may be provided on any analog or digital network(packet switched, circuit switched, or other scheme).

FIG. 2 is a block diagram of a system 210 configured in accordance withembodiments of the present technology. The system 210 includes severalcomponents including memory 211 (e.g., one or more computer readablestorage modules, components, devices). In some embodiments, the memory211 comprises one or more applications installed and/or operating on acomputer and/or a mobile device (e.g., the device 110 of FIG. 1, atablet, a smartphone, a PDA, a portable media player, or other“off-the-shelf” mobile device). The memory 211 can also be configured tostore information (e.g., audio data, subject information or profiles,environmental data, data collected from one or more sensors, mediafiles). A processor 212 (e.g., one or more processors or distributedprocessing elements) is coupled to the memory 211 and configured toexecute operations and/or instructions stored thereon.

A speaker 215 (e.g., the first transducer 115 and/or the speaker 125 ofFIG. 1) operatively coupled to the processor is configured to receiveaudio signals from the processor 212 and/or one or more other componentsof the system 210 and output the audio signals as sound (e.g., the sound105 of FIG. 1). In some embodiments, the speaker 215 includes aconventional dynamic loudspeaker disposed in a mobile device (e.g., asmartphone or tablet). In some embodiments, the speaker 215 includes anearphone transducer and/or a standalone loudspeaker. In otherembodiments, the speaker 215 includes a suitable transducer configuredto output acoustic energy in at least a portion of the human audiblefrequency spectrum (e.g., between about 20 Hz and 20 kHz).

A microphone 216 (e.g., the second transducer 116 and/or the microphone126 of FIG. 1) operatively coupled to the processor is configured toreceive sound, convert the sound into one or more electrical audiosignals and transmit the electrical audio signals to the memory 211and/or the processor 212. In some embodiments, the microphone 216includes a microphone disposed in a mobile device (e.g., a smartphone ortablet). In some embodiments, the microphone 216 is located on anearphone and/or along a cable connected to one or more earphones. Inother embodiments, the microphone 216 includes another suitabletransducer configured to receive acoustic energy in at least a portionof the human audible spectrum. Moreover, in some embodiments, thespeaker 215 and the microphone 216 are spaced apart by a distance (e.g.,2 cm or greater, between about 2 cm and 10 cm, between 4 cm and 8 cm, orat least about 6 cm). In other embodiments, however, the speaker 215 isimmediately adjacent the microphone 216. In certain embodiments, asingle transducer can transmit sound energy and receive sound energy. Infurther embodiments, the speaker 215 and/or the microphone 216 compriseone or more additional transducers to form one or more transducerarray(s). The transducer array(s) can be configured to transmit and/orreceive beamformed audio signals.

Communication components 213 (e.g., a wired communication link and/or awireless communication link (e.g., Bluetooth, Wi-Fi, infrared and/oranother wireless radio transmission network)) communicatively couple thesystem 210 to one or more communications networks (e.g., atelecommunications network, the Internet, a WiFi network, a local areanetwork, a wide area network, a Bluetooth network). A database 214 isconfigured to store data (e.g., audio signals and data acquired from asubject, equations, filters) used in the identification of movements ofa subject. One or more sensors 217 are configured to provide additionaldata for use in motion detection and/or identification. The one or moresensors 217 may include, for example, one or more ECG sensors, bloodpressure monitors, galvanometers, accelerometers, thermometers,hygrometers, blood pressure sensors, altimeters, gyroscopes,magnetometers, proximity sensors, barometers and/or hall effect sensors.

One or more displays 218 (e.g., the user interface 118 of FIG. 1)provide video output and/or graphical representations of data acquiredand processed by the system 210. A power supply 219 a (e.g., a powercable connected to a building power system, one or more batteries and/orcapacitors) provides electrical power to components of the system 210.In embodiments that include one or more batteries, the power supply 219a can be configured to recharge, for example, via a power cable,inductive charging, and/or another suitable recharging method.Furthermore, in some embodiments, the system 210 optionally includes oneor more other components 219 b (e.g., one or more microphones, cameras,Global Positioning System (GPS) sensors, Near Field Communication (NFC)sensors).

As explained in further detail below in reference to FIGS. 3-8C, thesystem 210 is configured to transmit sound toward a subject and receivesound reflected by the subject. The transmitted and received sound canbe used by the system 210 to detect movement of the subject and identifyone or more medical conditions (e.g., sleep apnea, COPD) in the subject.In some embodiments, for example, the memory 211 includes instructionsfor generating audio signals (e.g., FMCW audio signals that sweep fromabout 18 kHz to about 20 kHz or higher) and providing the generatedaudio signals to the speaker 215. The speaker 215 transmits the audiosignals as sound (e.g., acoustic energy comprising one or morewaveforms) and directs at least a portion of the transmitted soundtoward a subject (e.g., the subject 101 of FIG. 1) proximate the speaker215. A portion of the sound is reflected or backscattered toward themicrophone 216, which converts the sound into electrical audio signals.The memory 211 can further include instructions for processing theelectrical audio signals to detect motion of the subject (e.g., movementof the subject's chest and/or abdomen), to disambiguate between periodicmotion (e.g., respiratory motion) and non-periodic motion, and toidentify one or more medical conditions (e.g., an apnea event, COPD) inthe subject based on the detected motion of the subject. In someembodiments, an indication of the identified medical condition can beoutput to the display 218 and/or can be transmitted via thecommunication component 213 to a medical professional (e.g., a nurse, adoctor). In certain embodiments, the system 210 can be configured todetermine baseline breathing information (e.g., breathing frequency)about a subject and store the baseline breathing information. Thebaseline breathing information can be compared to subsequent breathingmeasurements to identify a respiratory disorder.

Suitable Methods

FIG. 3 is a flow diagram of a process 300 configured to detect an apneaevent in accordance with an embodiment of the present technology. FIG.4A is a graph 401 depicting an example of a motion waveform acquired bythe process 300 in accordance with an embodiment of the presenttechnology. FIG. 4B is a graph 402 depicting peaks detected in themotion waveform of FIG. 4A in accordance with an embodiment of thepresent technology.

Referring first to FIG. 3, the process 300 can comprise a set ofinstructions stored on memory (e.g., the memory 211 of FIG. 2) andexecuted by one or more processors (e.g., the processor 212 of FIG. 2).In some embodiments, the process 300 comprises one or more smartphoneapplications stored on a device (e.g., the device 110 of FIG. 1). Theprocess 300 begins at block 305 after the device and/or transducers arepositioned proximate a subject (e.g., 1 m away from the subject, betweenabout 0.5 m and 10 m from the subject, between about 1 m and 5 m fromthe subject) and/or the subject's bed (e.g., the bed 104 of the subject101 of FIG. 1). At block 305, the process 300 monitors the subject todetermine whether the subject is asleep. In some embodiments, forexample, the process 300 may monitor movements of the subject to detectrandom, non-periodic motions that the process 300 determines are notassociated with breathing motion of the subject. For example, if theprocess 300 detects a predetermined number of occurrences (e.g., two,three, four or higher) of non-periodic motion within a predeterminedtime period, (e.g., 5 minutes, 10 minutes, 20 minutes), the process 300may determine that the subject is awake for the duration of thepredetermined time period. Conversely, if the process 300 does notdetect the predetermined number of occurrences of non-periodic motionwithin the predetermined time period, the process 300 may determine thatthe subject is asleep during the entire predetermined time period.Collectively, a sum of a plurality of predetermined time periods that donot include the predetermined number of occurrences of detectednon-periodic motion may form the basis of an overall measurement ofsleep time during a session or test. Such an overall measurement ofsleep time may be used, for example, in the denominator of equation 1discussed above. In some embodiments, the process 300 is configured towait a predetermined amount of time (e.g., one hour, two hours, fourhours) before proceeding to the next step.

In some embodiments, the process 300 can detect an orientation of thedevice and, based on this detection, prompt a user to take correctiveaction. For example, the process 300 may provide more accurate detectionif a predetermined side of a measurement device (e.g., a front facingportion of the device 110 shown in FIG. 1) is oriented at apredetermined orientation relative to the subject. In some embodiments,for example, it may be preferable to have a side of the measurementdevice on which the speaker is located or most closely positioned to beoriented toward the subject. In embodiments in which the speaker and amicrophone are not on the same side of the measurement device, however,it may be desirable to acquire audio from the subject if a side of themeasurement device on which a microphone is positioned is facing uprightand/or substantially oriented toward the subject.

The process 300 can be configured to determine an orientation of themeasurement device using, for example, one or more sensing mechanisms(e.g., one or more gyroscopes, accelerometers, compass sensors). In someembodiments, for example, the one or more sensing mechanisms include oneor more of the sensors 217 discussed above with reference to FIG. 2. Insome embodiments, the process 300 can generate one or more audibleand/or visible indications instructing the subject and/or another userto take a corrective action based on the determined orientation. Thecorrective actions may include, for example, moving and/or orienting themeasurement device toward the location of the subject. In someembodiments, the process 300 may not proceed until one or morecorrective actions are detected. Alternatively, the one or more audibleand/or visible indications may persist while other blocks are executedin process 300. In some embodiments, the process 300 can be configuredto adjust detection thresholds based on a detected orientation.

At block 310, the process 300 generates one or more audio signals. Insome embodiments, the audio signals include FMCW signals having asawtooth waveform that includes a plurality of sweep audio signals or“chirps” that linearly sweep from a first frequency to a second, higherfrequency. In some embodiments, the chirps sweep from a first audiblefrequency (e.g., about 18 kHz) to a second audible frequency (e.g., 20kHz or higher). As those of ordinary skill in the art will appreciate,the frequency spectrum of a typical human ear ranges from 20 Hz to about20 kHz, and many transducers are configured for playback over thisspectrum. As humans age, however, the sensitivity of the ears to higherfrequencies typically diminishes such that sounds having frequenciesgreater than about 18 kHz are effectively inaudible for a typical adulthuman. Accordingly, selecting the first and second audible frequenciesto have a frequency equal to or greater than about 18 kHz allows fortransmission of sound over a conventional loudspeaker configured forplayback over the human audible frequency range while not disturbingmost adults as they sleep. In other embodiments, the chirps sweep from afirst audible frequency (e.g., 18 kHz) to a second inaudible frequency(e.g., a frequency greater than about 20 kHz and less than about 48 kHz,a frequency between about 22 kHz and about 44 kHz). In furtherembodiments, the chirps sweep between two frequencies outside the humanaudible range (e.g., greater than about 20 kHz and less than about 48kHz). Moreover, in some embodiments, the process 300 generates audiosignals comprising FMCW signals having a sine waveform, a trianglewaveform and/or a square waveform. In other embodiments, the process 300generates audio signals comprising pulse-modulated waveforms. In someembodiments, the process 300 generates audio signals using anothersuitable modulation method.

At block 320, the process 300 provides the generated audio signals to atransducer (e.g., the first transducer 115 of FIG. 1 and/or the speaker215 of FIG. 2) configured to convert the audio signals to acousticenergy (e.g., the sound 105 of FIG. 1) and further configured to directat least a portion of the acoustic energy toward the subject. At block330, the process 300 acquires echo data from a microphone (e.g., thesecond transducer 116 of FIG. 1 and/or the microphone 216 of FIG. 2) oranother transducer. The acquired echo data includes data correspondingto a portion of the sound transmitted toward the subject and reflectedor backscattered toward the microphone and converted by the microphoneto electrical signals.

Referring now to FIGS. 3, 4A and 4B together, at block 340 the process300 constructs a motion waveform using the echo data. The process 300analyzes the generated audio signals and the received echo data anddetects frequency shifts therebetween that are indicative of movement ofa portion of the subject's body (e.g., the subject's chest and/orabdomen). As explained in further detail below in reference to FIGS. 5A,5B and 6, the frequency shifts can be used to generate the motionwaveform as a function of time. One example of a motion waveformconstructed by the process 300 at block 340 is shown in the graph 401 ofFIG. 4A. The graph 401 includes a motion waveform 440 having a pluralityof peaks 444 and a plurality of valleys or nulls 446.

At block 350, the process 300 detects one or more of the peaks 444 inthe waveform 440 of FIG. 4A. The graph 402 of FIG. 4B shows one exampleof the peaks 444 detected by the process 300. Additional aspects ofconstruction of a motion waveform and detection of the peaks in thewaveform are described below in reference to FIG. 6.

At block 360, the process 300 analyzes the peaks (e.g., the peaks 444 ofFIGS. 4A and 4B) detected in the motion waveform (e.g., the waveform 440of FIG. 4A) to identify one or more sleep apnea events. For example, ifan amplitude of a particular peak in the waveform is less than or equalto a predetermined threshold amplitude, the process 300 may determinethat the particular peak corresponds to a hypopnea event in the subject.If, for example, successive peaks in the waveform are separated by apredetermined time (e.g., 10 seconds or greater), the process 300 maydetermine that the peak separation corresponds to a central apnea event.Further, if the process 300 detects a spike or a predetermined increase(e.g., 50%) in an amplitude between successive peaks, the process 300may determine that the peak increase corresponds to an obstructive apneaevent.

In some embodiments, the process 300 may compare a frequency of thedetected peaks to a predetermined breathing frequency (e.g., a priormeasurement of the patient's breathing frequency). The process 300 mayfurther determine a possible presence of a COPD exacerbation in thesubject if the frequency of the detected peaks is greater than equal toa predetermined percentage (e.g., between about 105% and about 125%, orabout 115%) of the predetermined breathing frequency. In someembodiments, the predetermined breathing frequency generally correspondsto a measured breathing frequency determined in a first portion orduration of a test, such as a predetermined period of time during asleep measurement (e.g., an initial 30 minutes of the sleepmeasurement). The process 300 can use the measured breathing frequencyas the subject's baseline breathing frequency. In other embodiments,however, the process 300 may use other predetermined percentages (e.g.,about 130% or higher) and/or other predetermined periods of time (e.g.,between about 15 minutes and about 30 minutes, between about 30 minutesand about 60 minutes, between about 60 minutes and about 120 minutes).

At block 370, the process 300 outputs an indication of one or more ofthe apnea events. In some embodiments, for example, the process 300 maystore one or more indications of apnea events in a memory or database(e.g., the memory 211 and/or the database 214 of FIG. 2). In someembodiments, the process 300 may output an indication of one or moreapnea events to a display (e.g., the user interface 118 of FIG. 1 and/orthe display 218 of FIG. 2).

FIG. 5A is a graph 501 depicting a conventional data acquisitionapproach in accordance with the prior art. FIG. 5B is a graph 502depicting a method of acquiring data in accordance with an embodiment ofthe present technology. Referring first to FIG. 5A, the graph 501includes a plurality of transmit signals 548 and a plurality ofcorresponding received signals 549. A fast fourier transform (FFT) iscomputed for each transmit/receive cycle.

Referring next to FIG. 5B, the graph 502 includes a plurality oftransmitted signals 550 (identified individually as a first transmittedsignal 550 a, a second transmitted signal 550 b, and an nth transmittedsignal 550 n) and a plurality of corresponding reflected signals 552(identified individually as a first reflected signal 552 a, a secondreflected signal 552 b, and an nth reflected signal 552 n). Theplurality of transmitted signals 552 comprise FMCW signals that linearlysweep between a first frequency f₀ (e.g., 18 kHz) and a second, higherfrequency f₁ (e.g., 20 kHz or higher) over a time T_(sweep) (e.g.,between about 5 ms and about 15 ms, between about 10 mins and about 11ms or about 10.75 ms).

The individual transmitted signals 550 are emitted from a loudspeaker(e.g., the first transducer 115 of FIG. 1) and a corresponding one ofthe reflected signals is received at a microphone (e.g., the secondtransducer 116 of FIG. 2) a period of time. For example, the firsttransmitted signal 550 a is emitted from a loudspeaker and thecorresponding first reflected signal 552 a is received a time delay Δtlater. The time delay Δt is given by:

$\begin{matrix}{{\Delta \; t} = \frac{2d}{Vsound}} & (2)\end{matrix}$

in which d is the distance between the loudspeaker and the subject andV_(sound) (i.e., approximately 340 m/s at sea level). Since thetransmitted frequency increases linearly in time, time delays in thereflected signals translate to frequency shifts in comparison to thetransmitted signals. The frequency shift Δf between individualtransmitted signals and the corresponding reflected signals is given bythe following:

$\begin{matrix}{{\Delta \; f} = {\frac{f_{1} - f_{0}}{Tsweep}\Delta \; t}} & (3)\end{matrix}$

With multiple reflectors at different distances from the receiver, theirreflections translate to different frequency shifts in the signal. AnFMCW receiver can extract all these frequency shifts (or demodulate thereflected signals) by performing a Fourier transform over one or morechirp durations. The chirp duration, Tsweep, is selected so that thereflections from all points within an operational distance (e.g., thedistance D of FIG. 1) preferably start arriving before the chirp ends.In one particular embodiment, for example, the operational distance isapproximately 1 meter, and a chirp duration of Tsweep 10.75 ms isselected. The act of breathing creates minute chest and abdomen motionthat can be captured by monitoring a corresponding bin in the Fouriertransform as a function of time. One challenge, however, is thatbreathing movements are relatively small and thus may cause a very smallfrequency shift. A 2 cm breathing displacement, for example, may resultin an 11.7 Hz frequency shift. Given a speed of sound of 340 m/s, a 48kHz sampling rate translates to a resolution of 0.71 cm per sample.Further, a 10.7 ms chirp duration corresponds to 512 samples. With 18-20kHz FMCW chirps, each sample corresponds to a 3.9 Hz frequency shift.Thus, a displacement of 0.71 cm can translate to a 3.9 Hz change in thefrequency domain. Consequentially, a 2 cm breathing movement can createan 11.7 Hz frequency shift.

A frequency shift of 11.7 Hz can present a challenge because at adistance of 1 m and with a chirp duration of 10.75 ms, the width of eachFFT bin is 93.75 Hz, which is much greater than the frequency shiftscreated due to breathing. To extract the minute frequency shifts createdby breathing motion, an FFT is computed over an integer number of chirpdurations as shown in FIG. 5B. This is in contrast to a traditional FMCWreceiver that computes a Fourier transform over the duration of a singleFMCW chirp as shown, for example in FIG. 5A. Computing an FFT over Nchirps decreases a width of each FFT bin by a factor of N. In oneembodiment, an FFT computed over ten chirps results in an FFT bin widthof 9.37 Hz, allowing the capture of the 11.7 Hz frequency shiftsresulting from the breathing movements.

FIG. 6 is a flow diagram of a process 600 configured to identify motionin accordance with an embodiment of the present technology. The process600 begins at block 610 with monitoring a plurality of transmit/receivecycles as described above in reference to FIG. 5B. The process 600receives a plurality of reflected signals (e.g., the reflected signals552 of FIG. 5) and computes a plurality of primary frequency transformsover a predetermined number N (e.g., 5, 10, 20, 40, 50) of chirps ortransmit/receive cycles. As those of ordinary skill in the art willappreciate, a frequency transform converts and/or demodulates a signalfrom a first domain (e.g., a time domain) to a frequency domain. Theprimary transforms computed by the process 600 at block 610 representfrequency spectra of the reflected signals in a plurality of frequencybins. Each bin represents a discrete portion (e.g., about 1 Hz to about100 Hz, about 5 Hz to about 50 Hz, about 8 Hz to about 12 Hz, about 9 Hzto about 10 Hz) of the frequency spectrum of the reflected signals. Insome embodiments, for example, the process 600 computes a plurality of5120-point FFTs over every series of 10 reflected signals received bythe process 600. In one particular embodiment, for example, each bin ofthe primary transforms has a bandwidth of approximately 9.37 Hz.

At block 620, the process 600 computes a secondary frequency transform(e.g., an FFT) of an individual bin of each the primary transformscomputed at block 610 over a predetermined time duration (e.g., 5 s, 10s, 30 s, 60 s, 5 minutes, 10 minutes). When the process 600 initiallyproceeds to block 620, an index value m is set to 1. Accordingly, theprocess 600 performs an FFT of the 1^(st) bin of a plurality of theprimary transforms as a function of time. In some embodiments, forexample, the process 600 computes a 24,000-point FFT of the 1^(st) binsof a plurality of primary transforms over time duration of 30 seconds.

At decision block 630, the process 600 analyzes the secondary transformcalculated at block 620 to determine whether the second transformincludes one or more peaks associated with breathing frequencies. Insome embodiments, for example, the process 600 analyzes the secondarytransform from block 620 to determine if any peaks are detected betweenabout 0.1 Hz or about 0.5 Hz (e.g., between about 0.2 Hz and about 0.3Hz), which is a range that includes typical human breathing frequencies.If no peaks are detected at or near these frequency values, then theprocess 600 returns to block 620 and adds 1 to the index value m (i.e.,m+1). The process 600 computes a new secondary transform at block 620 atthe next bin m of the primary transforms over a predetermined period oftime. The process 600 continues to iteratively compute secondarytransforms until the process 600 detects peaks corresponding tobreathing frequencies and/or until a predetermined value of m (e.g., 58,60, 100, 200) is reached. If the process 600 detects a peak betweenabout 0.1 Hz and about 0.5 Hz, the process 600 stores the index mcorresponding to the bin number in which the peak is detected asm_(peak), and proceeds to block 640.

At block 640, the process 600 extracts motion data from the reflectedaudio signals. In some embodiments, the process 600 continues to computea plurality of the primary transforms of the reflected audio and computea secondary transform of bin m_(peak) of the primary transforms as afunction of time. The process 600 can also compute a distance D betweena measurement device (e.g., the device 110 of FIG. 1) and the subjectusing the m_(peak) index obtained by the process 600 at block 640. Forexample, if the bandwidth of each bin is approximately 9.37 Hz, and binindex m_(p) obtained at block 630 is 58 (i.e., breathing motion detectedin the 58^(th) bin of the primary transform of block 610), the resultingfrequency shift caused by movement of the subject is approximately 1,087Hz (9.37 Hz*58*2). Using equation 2 above, the time delay can beobtained as approximately 5.8 ms, which corresponds to a distance ofabout 1 m from the subject.

At block 650, the process 600 constructs a motion waveform (e.g. themotion waveform 440 of FIG. 4A) of movement of the subject's chestand/or abdomen as a function of time using the secondary transformcomputed at block 640. At block 660, the process 600 ends.

FIG. 7 is a flow diagram of a process 700 configured to identify anapnea event in accordance with an embodiment of the present technology.At block 710, the process analyzes peak in a motion waveform (e.g., thepeaks 444 detected in the motion waveform 440 of FIG. 4A). In someembodiments, the process 700 is configured to determine a pose (e.g.,supine, prone, non-prone, sitting up, lying down) of the subjectcorresponding to one or more of the detected peaks. The process 700 canbe configured, for example, to monitor a distance (e.g., the distance Dof FIG. 1) and/or an orientation between a measurement device (e.g., thedevice 110 of FIG. 1) and the subject. In certain embodiments, forexample, the process 700 can detect one or more aperiodic portions ofthe motion waveform. The process 700 can associate the one or moredetected aperiodic portions of the subject's motion waveform with one ormore non-breathing motions (e.g., rolling over, sitting up). If, forexample, the subject rolls from one side of her body to another, theresulting motion waveform can arrive from a slightly different distance.By tracking the motion and the distance from which the breathing signalappears, the process 700 can determine an orientation of the subject.The process 700 can be further configured to use the subject'sorientation information to detect positional sleep apnea in the subject.In some embodiments, the process 700 can be configured to distinguishbetween sleep apnea in, for example, a supine position (i.e., thesubject lying with her face generally upward or away from a bed), aprone position (i.e., the subject lying with her face generally downwardor toward the bed), and/or another position or pose. In someembodiments, the positional information determined by the process 700 atblock 710 can be used in subsequent blocks discussed below. Inadditional embodiments, the process 700 may determine a position ororientation of the subject relative to the measurement device at one ormore other blocks of the process 700.

At decision block 720, the process 700 determines whether one or morepeaks in the motion waveform are less than a predetermined threshold(e.g., an amplitude 30% less than other peaks in the motion waveform)over a predetermined time duration (e.g., between about 5 s and 60 s, orabout 10 s). If the process 700 determines that plurality of peaks arein the motion waveform are less than the predetermined threshold overthe predetermined time, the process 700 outputs an indication of ahypopnea event at block 725. Otherwise, the process 700 proceeds toblock 730.

At block 730, the process 700 determines whether successive peaks in themotion waveform are separated by a time duration greater than apredetermined threshold time (e.g., 10 seconds). If the process 700detects successive peaks in the motion waveform separated by thepredetermined threshold time or greater, the process 700 outputs anindication of a central apnea event at block 735. Otherwise, the process700 proceeds to block 740.

At decision block 740, the process 700 determines whether successivepeaks in the motion waveform include a first peak and a second,following peak in which the amplitude of the second peak is apredetermined percentage (e.g., 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%or higher) greater than an amplitude of the first peak. If the processdetects successive peaks in the motion waveform in which the second peakhas an amplitude greater than the predetermined percentage of the firstpeak, the process 700 outputs an indication of an obstructive apneaevent at block 745. In some embodiments, the process 700 may insteaddetect a first peak and a second, following peak in which the secondpeak is a predetermined percentage (e.g., 30%, 40%, 50%, 60%, 70%, 80%,90%) less than the first peak. At decision block 750, the process 700determines whether there are additional peaks in the motion waveform. Ifthere are additional peaks in the motion waveform, the process 700returns to block 710. Otherwise, the process 700 ends at block 760.

FIGS. 8A-8C show examples of apnea/hypopnea events that may beidentified by the process 700 (FIG. 7) in accordance with an embodimentof the present technology. FIG. 8A, for example, is a graph 801depicting one example of a central apnea event described above withreference to block 730 of FIG. 7. A chest motion waveform 840 a includesa pair of successive peaks 844 a and 844 b separated by time T₁ (e.g.,about 15 s) greater than a predetermined central apnea threshold time(e.g., about 1 Os).

FIG. 8B is a graph 802 depicting one example of hypopnea event describedabove with reference to block 720 of FIG. 7. A motion waveform 840 bincludes a plurality of peaks, including a first peak 845 a, a secondpeak 845 b, and a third peak 845 c. The first peak 845 a and the secondpeak 845 b comprise a plurality of peaks in the waveform 840 b havingamplitudes less than a predetermined threshold amplitude (e.g., 30% lessthan an amplitude of the peak 845 c) during a predetermined timeduration T₂ (e.g., about 35 s).

FIG. 8C is a graph 803 depicting one example of an obstructive apneaevent described above with reference to block 740 of FIG. 7. A motionwaveform 840 c includes a plurality of peaks, including a first peak 846a and, a second peak 846 b. The second peak 846 b has an amplitude thatis AL (e.g., 40%, 50%, 75%) greater than the first peak 846 a or anyother peaks in the waveform 840 c preceding the second peak 846 b by atime T₃ and/or following the second peak 846 b by a time T₄.

The disclosure may be defined by one or more of the following examples:

1. A method of operating a device to identify sleep apnea events in asubject, the method comprising:

-   -   transmitting sound energy toward the subject using a first        transducer on the device, wherein the transducer is configured        to generate sound energy over a range of frequencies that        includes frequencies less than 20 kHz;    -   receiving echoes from the subject corresponding to the        transmitted sound energy using a second transducer on the        device, wherein the second transducer is configured to produce        electrical signals corresponding to the received echoes;    -   generating a waveform using the electrical signals; detecting a        plurality of peaks in the waveform, wherein individual peaks        have a corresponding amplitude and frequency, and further        wherein individual peaks are indicative of breathing motion of        the subject; and    -   outputting an indication of a sleep apnea event for each        occurrence of a period of time between successive individual        peaks in the waveform exceeding a predetermined threshold time.

2. The method of example 1 wherein transmitting the sound energycomprises emitting a plurality of audio chirps from the firsttransducer, and wherein individual audio chirps linearly sweep from afirst frequency to a second, higher frequency over a predetermined timeduration.

3. The method of example 2 wherein the first frequency is about 18 kHzand the second frequency is 20 kHz or greater.

4. The method of examples 2 or 3 wherein at least a portion of theplurality of audio chirps comprise frequency-modulated continuous-wavesound signals emitted from the first transducer.

5. The method of any of examples 2-4 wherein generating the waveformcomprises performing a Fourier transform of the emitted audio chirps andthe corresponding received echoes over a period of time longer than thepredetermined time duration of the individual chirps.

6. The method of example 5 wherein the period of time is approximately10 times the predetermined time duration of the individual chirps orlonger.

7. The method of any of examples 1-6, further comprising repeating thetransmitting and receiving for a plurality of transmit/receive cycles,wherein generating the waveform further comprises determining aplurality of frequency shifts between the transmitted sound energy andthe corresponding received echoes for each of the plurality oftransmit/receive cycles.

8. The method of any of examples 1-7 wherein generating the waveformcomprises filtering out signals having a frequency less than about 18kHz.

9. The method of any of examples 1-8, further comprising outputting anindication of a sleep apnea event for each occurrence of an individualpeak in the waveform having an amplitude less than or equal to apredetermined threshold amplitude and time period.

10. The method of example 9, further comprising outputting an indicationof a sleep apnea event for each occurrence of an increase of 50% orgreater of the amplitudes of successive individual peaks in thewaveform.

11. The method of example 10, further comprising outputting thesubject's apnea-hypopnea index, wherein outputting the subject'sapnea-hypopnea index comprises determining a ratio of a total number ofsleep apnea events during a sleep cycle of the subject and a duration ofthe sleep cycle of the subject.

12. The method of any of examples 1-11 wherein transmitting sound energycomprises transmitting sound energy having a wavelength greater than onehalf of a distance between the first transducer and the secondtransducer.

13. A method of operating an electronic device to monitor movements of asubject proximate the electronic device, the method comprising:

-   -   emitting a plurality of audio sweep signals toward the subject        from a loudspeaker operatively coupled to the electronic device,        wherein individual audio sweep signals linearly sweep from a        first frequency less than 20 kHz to a second, higher frequency        over a predetermined time duration;    -   acquiring audio data at a microphone operatively coupled to the        electronic device, wherein the audio data comprises echo signals        that correspond to individual audio sweep signals backscattered        by the subject toward the microphone;    -   processing the emitted audio sweep signals and the acquired        audio data to generate a motion waveform; detecting one or more        peaks in the motion waveform, wherein individual peaks are        indicative of movements of the subject; and    -   outputting an indication of movement of the subject based one or        more of the detected peaks.

14. The method of example 13 wherein the first frequency is about 18 kHzand the second frequency is 20 kHz or greater, and further wherein atleast portion of the plurality of the audio sweep signals comprisefrequency-modulated continuous-wave sound signals.

15. The method of examples 13 or 14 wherein the processing furthercomprises:

-   -   calculating a plurality of frequency domain representations of        the emitted audio sweep signals and the echo signals, wherein        the frequency domain representations are calculated over a time        period lasting a predetermined multiple of the predetermined        time duration of the individual audio sweep signals; and    -   determining a frequency shift in the individual frequency domain        representations relative to the first frequency.

16. The method of any of examples 13-15 wherein the individual peaks areindicative of movement of the chest and/or abdomen of the subject,wherein the individual peaks have a corresponding amplitude, and whereinoutputting an indication of movement of the subject further comprisesoutputting an indication of a sleep apnea event for each occurrence of aperiod of time between successive individual peaks in the motionwaveform exceeding a predetermined threshold time.

17. The method of example 16 wherein outputting an indication ofmovement of the subject further comprises outputting an indication of asleep apnea event for each occurrence of an individual peak in thewaveform having an amplitude less than or equal to a predeterminedthreshold amplitude.

18. The method of examples 16 or 17 wherein outputting an indication ofmovement of the subject further comprises outputting an indication of asleep apnea event for each occurrence of an increase of 50% or greaterof the amplitudes of successive individual peaks in the waveform.

19. The method of any of examples 13-18, further comprising:

-   -   comparing a frequency of the detected peaks to a predetermined        breathing frequency, wherein outputting an indication of        movement of the subject comprises outputting an indication of a        possible presence of chronic obstructive pulmonary disease in        the subject if the frequency of the detected peaks is greater        than equal to 115% of the predetermined breathing frequency.

20. A computer program product comprising a non-transitory computerreadable storage medium storing computer usable program code executableto perform operations for outputting an indication of a sleep apneaevent in a subject, the operations comprising:

-   -   transmitting a plurality of chirp signals to a first transducer        operatively coupled to a mobile device, wherein individual chirp        signals linearly sweep from a first frequency less than 20 kHz        to a second, higher frequency over a predetermined time        duration;    -   acquiring echo data from a second transducer operatively coupled        to the mobile device, wherein the echo data includes data        corresponding to individual chirp signals reflected by the        subject toward the second transducer;    -   demodulating the acquired echo data to obtain a motion signal        indicative of respiratory motion of the subject;    -   detecting one or more amplitude peaks in the motion signal; and    -   outputting an indication of a sleep apnea event if a period of        time between successive individual amplitude peaks in the motion        signal exceeds a predetermined threshold time.

21. The computer program product of example 20 wherein the operationsfurther comprise repeating the transmitting and acquiring for apredetermined number of transmit/acquisition cycles, whereindemodulating the acquired echo data comprises performing a singleFourier transform of the predetermined number of transmit/acquisitioncycles.

The above detailed descriptions of embodiments of the technology are notintended to be exhaustive or to limit the technology to the precise formdisclosed above. Although specific embodiments of, and examples for, thetechnology are described above for illustrative purposes, variousequivalent modifications are possible within the scope of thetechnology, as those skilled in the relevant art will recognize. Forexample, while steps are presented in a given order, alternativeembodiments may perform steps in a different order. The variousembodiments described herein may also be combined to provide furtherembodiments applicable to a wide range of human physiological behaviorsand illnesses.

Moreover, unless the word “or” is expressly limited to mean only asingle item exclusive from the other items in reference to a list of twoor more items, then the use of “or” in such a list is to be interpretedas including (a) any single item in the list, (b) all of the items inthe list, or (c) any combination of the items in the list. Where thecontext permits, singular or plural terms may also include the plural orsingular term, respectively. Additionally, the term “comprising” is usedthroughout to mean including at least the recited feature(s) such thatany greater number of the same feature and/or additional types of otherfeatures are not precluded. It will also be appreciated that specificembodiments have been described herein for purposes of illustration, butthat various modifications may be made without deviating from thetechnology. Further, while advantages associated with certainembodiments of the technology have been described in the context ofthose embodiments, other embodiments may also exhibit such advantages,and not all embodiments need necessarily exhibit such advantages to fallwithin the scope of the technology. Accordingly, the disclosure andassociated technology can encompass other embodiments not expresslyshown or described herein.

I/We claim:
 1. A method of operating an electronic device to identifysleep apnea events in a subject, the method comprising: transmittingsound energy toward the subject using a first transducer on theelectronic device, wherein the transducer is configured to generatesound energy over a range of frequencies that includes frequencies lessthan 20 kHz; receiving echoes from the subject corresponding to thetransmitted sound energy using a second transducer on the electronicdevice, wherein the second transducer is configured to produceelectrical signals corresponding to the received echoes; generating awaveform using the electrical signals; detecting a plurality of peaks inthe waveform, wherein individual peaks have a corresponding amplitude,and further wherein individual peaks are indicative of breathing motionof the subject; and outputting an indication of a sleep apnea event foreach occurrence of a period of time between successive individual peaksin the waveform exceeding a predetermined threshold time.
 2. The methodof claim 1 wherein transmitting the sound energy comprises emitting aplurality of audio chirps from the first transducer, and whereinindividual audio chirps linearly sweep from a first frequency to asecond, higher frequency over a predetermined time duration.
 3. Themethod of claim 2 wherein the first frequency is about 18 kHz and thesecond frequency is 20 kHz or greater.
 4. The method of claim 2 whereinat least portion of the plurality of audio chirps comprisefrequency-modulated continuous-wave sound signals emitted from the firsttransducer.
 5. The method of claim 2 wherein generating the waveformcomprises performing a Fourier transform of the electrical signalscorresponding to the received echoes over a period of time longer thanthe predetermined time duration of the individual chirps.
 6. The methodof claim 5 wherein the period of time is approximately 10 times thepredetermined time duration of the individual chirps or longer.
 7. Themethod of claim 1, further comprising repeating the transmitting andreceiving for a plurality of transmit/receive cycles, wherein generatingthe waveform further comprises determining a plurality of frequencyshifts between the transmitted sound energy and the correspondingreceived echoes for each of the plurality of transmit/receive cycles. 8.The method of claim 1 wherein generating the waveform comprisesfiltering out signals having a frequency less than about 18 kHz.
 9. Themethod of claim 1, further comprising outputting an indication of asleep apnea event for each occurrence of an individual peak in thewaveform having an amplitude less than or equal to a predeterminedthreshold amplitude.
 10. The method of claim 9, further comprisingoutputting an indication of a sleep apnea event for each occurrence ofan increase of 50% or greater of the amplitudes of successive individualpeaks in the waveform.
 11. The method of claim 10, further comprisingoutputting the subject's apnea-hypopnea index, wherein outputting thesubject's apnea-hypopnea index comprises determining a ratio of a totalnumber of sleep apnea events during a sleep cycle of the subject and aduration of the sleep cycle of the subject.
 12. The method of claim 1wherein transmitting sound energy comprises transmitting sound energyhaving a wavelength greater than one half of a distance between thefirst transducer and the second transducer.
 13. A method of operating anelectronic device to monitor movements of a subject proximate theelectronic device, the method comprising: emitting a plurality of audiosweep signals toward the subject from a loudspeaker operatively coupledto the electronic device, wherein individual audio sweep signalslinearly sweep from a first frequency less than 20 kHz to a second,higher frequency over a predetermined time duration; acquiring audiodata at a microphone operatively coupled to the electronic device,wherein the audio data comprises echo signals that correspond toindividual audio sweep signals backscattered by the subject toward themicrophone; processing the acquired audio data to generate a motionwaveform; detecting one or more peaks in the motion waveform, whereinindividual peaks are indicative of movements of the subject; andoutputting an indication of movement of the subject based one or more ofthe detected peaks.
 14. The method of claim 13 wherein the firstfrequency is about 18 kHz and the second frequency is 20 kHz or greater,and further wherein at least portion of the plurality of the audio sweepsignals comprise frequency-modulated continuous-wave sound signals. 15.The method of claim 13 wherein the processing further comprises:calculating a plurality of frequency domain representations of theemitted audio sweep signals and the echo signals, wherein the frequencydomain representations are calculated over a time period lasting apredetermined multiple of the predetermined time duration of theindividual audio sweep signals; and determining a frequency shift in theindividual frequency domain representations relative to the firstfrequency.
 16. The method of claim 13 wherein the individual peaks areindicative of movement of the chest of the subject, wherein theindividual peaks have a corresponding amplitude, and wherein outputtingan indication of movement of the subject further comprises outputting anindication of a sleep apnea event for each occurrence of a period oftime between successive individual peaks in the motion waveformexceeding a predetermined threshold time.
 17. The method of claim 16wherein outputting an indication of movement of the subject furthercomprises outputting an indication of a sleep apnea event for eachoccurrence of an individual peak in the waveform having an amplitudeless than or equal to a predetermined threshold amplitude.
 18. Themethod of claim 16 wherein outputting an indication of movement of thesubject further comprises outputting an indication of a sleep apneaevent for each occurrence of an increase of 50% or greater of theamplitudes of successive individual peaks in the waveform.
 19. Themethod of claim 13 further comprising: comparing a frequency of thedetected peaks to a predetermined breathing frequency, whereinoutputting an indication of movement of the subject comprises outputtingan indication of a possible presence of chronic obstructive pulmonarydisease in the subject if the frequency of the detected peaks is greaterthan equal to 115% of the predetermined breathing frequency.
 20. Acomputer program product comprising a non-transitory computer readablestorage medium storing computer usable program code executable toperform operations for outputting an indication of a sleep apnea eventin a subject, the operations comprising: transmitting a plurality ofchirp signals to a first transducer operatively coupled to a mobiledevice, wherein individual chirp signals linearly sweep from a firstfrequency less than 20 kHz to a second, higher frequency over apredetermined time duration; acquiring echo data from a secondtransducer operatively coupled to the mobile device, wherein the echodata includes data corresponding to individual chirp signals reflectedby the subject toward the second transducer; demodulating the acquiredecho data to obtain a motion signal indicative of respiratory motion ofthe subject; detecting one or more amplitude peaks in the motion signal;and outputting an indication of a sleep apnea event if a period of timebetween successive individual amplitude peaks in the motion signalexceeds a predetermined threshold time.
 21. The computer program productof claim 20 wherein the operations further comprise: repeating thetransmitting and acquiring for a predetermined number oftransmit/acquisition cycles, wherein demodulating the acquired echo datacomprises performing a single frequency transform of the echo datareceived during the predetermined number of transmit/acquisition cycles.